Speaker 1we're just getting started. This seems to be accelerating at an unprecedented pace. We haven't seen revenue growth like this in our lifetime. We went zero, 12, 50, 200, and we'll finish this year north of 500. We need to get to a billion dollars of ARR as quickly as possible. I'd put the over-under at December 2027, and I would take the under. We could take the company public next
Speaker 2year if we wanted to. This is a very special 20VC with me, Harry Stebbings. The show you're about to listen to, oh, it was not filmed in the usual recording studio. No, no. We went to Craven Cottage, the home of Fulham football. Why? Well, our guest today just got front of shirt sponsorship for Craven Cottage and for Fulham, most importantly, the team that play there. Welcome Aaron Katz, founder and CEO of ClickHouse, industry-leading online analytical processing database management system. Try saying that after a couple of tequilas. But they've just crossed 350 million in ARR. They have customers. Microsoft, Anthropic, OpenAI, Tesla, Netflix. If you're a great company, you kind of use ClickHouse. And Aaron is incredible. He was one of the leading execs at Elastic for years. Before that, he spent 12 years working with the one and only Benioff at Salesforce. Now, he's obviously the co-founder of ClickHouse, which is worth over $15 billion. I cannot wait for you to hear this discussion. It was so much fun for me to sit down with a dear friend in ARR. But before we dive into the show today, founders face a different set of challenges at every stage of growth. For Sid Shate, co-founder and CEO of D-Matrix, J.P. Morgan delivered the guidance and expertise to help navigate what came next. He credits J.P. Morgan's high-touch approach with supporting D-Matrix as it grew and expanded internationally. Whether you're in the early days or expanding into new markets, J.P. Morgan helps startups navigate complexity with real confidence, offering personalized guidance and deep sector expertise. Find out how J.P. Morgan helps founders at jpmorgan.com forward slash grow without limits. J.P. Morgan is the bank of the innovation economy. While J.P. Morgan powers your finances, Asana keeps the work moving. Most companies have tried AI. Most aren't seeing results. Not because AI doesn't work. It's because AI hasn't reached the workflows that it needs to. That's the gap Asana is built to close. Asana is the operating system for human agent teams, your easy button for AI productivity across every team. Ready-to-go AI teammates, pre-built for marketing, ops, and IT. No prompt engineering, no setup. They show up where the work is happening, already onboarded, in your workflows, ready to deliver. With Asana, your whole company can work on the same plan towards the same goal, whether you're a team of 10 or a team of 10,000. Asana, where humans, and agents work flow together. Try it at asana.com. That's A-S-A-N-A dot com. While Asana aligns the roadmap, Base44 helps you build faster. You have the idea, but with most AI tools, you hit a wall. The setup, the config, the gap between what you pictured and what you actually ship. Well, Base44 is where that wall disappears. You describe it? Yeah, Base44 builds it. Apps, websites, AI agents, real working products, built in minutes, using nothing but plain language. And it's all batteries included. The backend, the database, the authentication, the hosting, the heavy lifting is handled. So you just really stay in the flow. This doesn't just take the busy work off your plate, but it gives you an advantage and pushes you past what you thought you could build alone. So in this market, fast is the baseline. To win, you just have to be first. Base44 is that edge, the move that skips the troubleshooting and gets you straight to the breakthrough. Build your next thing at Base44.com. That's Base44.com. You have now arrived at your destination. Aaron, dude, I've done over a thousand shows. I've never had a setting quite like this for a show. So thank you so much for hosting at Fulham Football Club. Yeah, total joy. Now, I want to start with just a little explainer on what is ClickHouse and what does ClickHouse become in a five-year period? Just to set the
Speaker 1scene there. Yeah, well, as one of our more recent investors, I think you understand the idea of ClickHouse. ClickHouse is a company that's been around for a long time. And it satisfies a very broad array of use cases. And it's used by nearly every AI-native company, anthropic, open AI, weights and biases. It's known for its lightning-fast query execution, extreme resource efficiency in terms of storing vast volumes of data. And when we look at, bluntly, the fastest
Speaker 2growing AI companies, I think the single biggest question that I have right now is, where are we in the cycle? You know, I'm really good friends with very smart people. I think at Harry, I've seen this before. The levels of debt that we're seeing is insane. The prices and the valuations are so exuberant. And then I also look at adoption and revenue scaling. And I have these two
Speaker 1paradoxical data points. We're just getting started. You know, one of the few benefits of age is experience. And so I've been through a few of these before in terms of the internet and mobile and social. How does it actually compare as a builder? Because we hear a lot of pontifications from venture investors. How does it compare for you? Those cycles, in my experience, were much more gradual. This seems to be accelerating at an unprecedented pace in terms of how quickly these prices are maturing and how quickly these companies are growing. I mean, we haven't seen revenue growth like this in our lifetime. And the demands on the systems of these agentic applications is unlike
Speaker 2anything we've ever seen. Totally agree with you there in terms of the revenue scaling. A lot of people always look to pick holes. One of the holes they often pick in the revenue scaling is the gross margin profile. Do we just see a new world of lower gross margins? When we look at companies like Fireworks, Lynn was on the show and she was like, yeah, we're at 30, 35%. We hope to be more global in the world. Or do we actually scale into traditional SaaS margins over time?
Speaker 1You know, a lot of these companies just seem to have unlimited access to capital right now. And they're growing so quickly that I think they can operate with gross margins that most public company investors would not be satisfied with. I think as long as they can demonstrate a path to margin expansion over the course of the next few years, while still growing at these unprecedented levels with very healthy balance sheets, I worry less about gross margins like we did five years ago in
Speaker 2traditional enterprise software. What should I worry about then as an investor? As I think about navigating this new world, again, you have the best customer base that you could almost ask for. I was talking about some of the fast-growing companies on our walk the other day and you're like, well, they're both customers. And it was just universal, the best companies we use in ClickHouse. What should I be concerned about, worry about when I'm investing today looking at
Speaker 1these names? If you were to say, what's the single biggest risk would be durability of revenue, because the switching costs that you and I talked about are very high for, infrastructure software. The switching costs can be very low for agentic applications. And we're seeing that with these model providers that are leapfrogging one another, what seems like every other week. I would call into question the durability of some of the revenue for some of these
Speaker 2AI applications. When I look at like an anthropic IPO at 2 trillion and you look at Cloud Code being the kind of dominant Trojan horse behind that, would that not fall into the low switching cost?
Speaker 1I would put it in that category. That's not showing up in our use of Cloud Code because our anthropic spend is not showing up in our use of Cloud Code because our anthropic spend is up a hundred times from what it was at the beginning of the year. Can I ask, how much do you spend on anthropic? A significant amount. We weren't doing enough at the turn of the calendar year. So I sent an email to the company and the subject was the AI awakening. And I said, I think we're moving too slowly. And I'm not seeing the adoption of these coding applications, for example, that I would expect to see for a leading database provider like ClickHouse. And the company rallied to the call and we've seen just this explosive growth in terms of our use of these applications. And we're now looking at adopting more open weights models, whereas just the traditional frontier labs. But I think anthropic specifically and open AI have the benefit of being both a model provider and the harness provider that the open weights models right now are behind in.
Speaker 2Do you think that is the right approach? Do you not think it's better to be independent because then you can actually do optimal model routing for different tasks versus being tied into one model provider because they are your harness also?
Speaker 1Yeah. I mean, for example, some of these open weights models we'll use for code review, but we won't necessarily use to ship production code because we have concerns about the output
Speaker 2inference. Totally. Yeah. You said there about, I love this, the AI awakening. The challenge then becomes, and we had the president of Uber on the show who was much more skeptical of the ROI that it generated internally. How do you think about token budgeting cost when suddenly you're incentivizing this, hey, run free, and then the bill might come at the end of the quarter?
Speaker 1Well, the primary measure that we care about, as you know, is revenue growth. And if we see the sustained revenue growth that we've experienced over the last three years, and we're a very efficient company, as you know, some would argue we're too efficient, then I worry less about the expense that we're incurring on coding agents, for example, because we're covering a very broad surface area and our roadmap is accelerating at a pace that we've never seen before. And as long as we can continue to ship features that satisfy this very broad set of use cases, then I can always rein in token consumption. And the cost of tokens, as we know, is going down. Not up. And so they're becoming more efficient, not less efficient. But our revenue is growing faster than it ever has. So I'll take that trade any day of the week.
Speaker 2You said that you're too efficient in some people's eyes. Where should you have spent where you didn't spend? And how do you reflect on that?
Speaker 1So we've got about 100 quota-carrying salespeople, for example. And I think you know our revenue scale is significantly more than 100 million. And so our average rep productivity is quite high relative to the industry average. Our competitors that we're going up against, some of these very large data warehousing companies, some of these very large observability companies, have thousands of salespeople. They wake up every morning thinking about one specific use case. Our salespeople wake up every morning thinking about, 10 different use cases. And there's only 100 of them going up against an army of 2,000, 3,000 sellers for some of these very large data warehousing companies. So I think the one thing, and if I look back over the last two years, that I wish I had done differently was increasing sales
Speaker 2capacity. That's so interesting. And so you should have invested more in sales team sales leaders
Speaker 1earlier. Well, I really wanted the pressure for the first few years to be on product and engineering because I looked at the two most popular infrastructure software companies over the last 10 years. And I distill that down to Datadog and Snowflake. They were both successful, but through very different avenues. Datadog had this PLG self-service developer-led motion. So you could get started, deploy an agent, instrument your application, never talk to anybody in sales. Snowflake went heavy after the enterprise through very expensive sales and marketing. I just thought it was going to be a lot easier to follow the Datadog playbook than the Snowflake playbook. And it proved to be the case. But at some point you need to layer in an enterprise sales motion on top of some sort of data. And I think that's a really good point.
Speaker 2What do you know now about layering on that enterprise sales motion that you wish you'd
Speaker 1known before you started? You know, I spent 12 years at Salesforce. And so I was kind of a student of Mark Benioff's playbook and so many lessons learned through that experience. And this was a long time ago. I joined that company 24 years ago. What was your biggest lesson from working with him? If there was one takeaway? That you can overestimate what you can achieve in one year and underestimate what you can achieve in five. When I started, it was a three-year-old startup and it was basically a glorified contact man. You know, Salesforce automation. We essentially said what you're traditionally using ACT or Goldmine or using a spreadsheet, you can use Salesforce for. But Mark had this bigger vision and he said, we're going after Siebel, SAP, Oracle, Microsoft. We didn't have the product set to go after those competitors, but he was such an incredible marketer that he created this perception in the industry that some of the largest companies in the world could adopt this technology and that we would deliver on a roadmap that would satisfy the requirements over time. And he did.
Speaker 2You said the word roadmap multiple times in different contexts there. But I do a show every week with Jason Lampkin and Maria O'Driscoll. It's very successful and popular, which is fun. But Jason said last week that if you are not well into your 2027 roadmap already, you are behind. Are you seeing dev acceleration because of AI tooling? And how do you measure actual ROI internally when attribution is really difficult?
Speaker 1Yeah, we're shipping products faster than we ever have. We're entering new product categories two years ahead of where we thought we would. Really? Yeah, both organically and inorganically. We've had six acquisitions over the last four years that have propelled us into new use case areas. And our organic roadmap, shipping features like stateless workers, which is essentially infinite compute, we've shipped those faster than we ever thought possible.
Speaker 2How do you think, and Nikesh Palalto is a very good friend of mine. He's a very brilliant M&A machine. How do you think about the buy versus build versus distraction? What's that internal decision maker for you when you think about those six acquisitions?
Speaker 1If I think that our product and engineering teams can innovate, we're going to be able to do that. We're going to be able to do that. We're going to be able to innovate in a specific area that we're not in today, then I'll let that play out organically. If I see a founder or a group of founders that are building on top of ClickHouse, that are getting into a category that I think is going to be a future component of what we build as an ultimate data platform, then I think about doing something inorganically. We partnered again with six different founders, actually more than that. Some of these companies have multiple founders. Our most recent one earlier this year was LangFuse out of Berlin, which is three incredible founders. And I think that's going to be something that we're going to see. And I think that's going to be something that we're going to see. And I think that's going to be something that we're going to see. Every enterprise in the world is going to need this technology.
Speaker 2In terms of the agentic future that we face, how does software and product decisions change when you no longer cater to humans, but you cater to agents?
Speaker 1Well, even four or five years ago, software applications were designed for a specific persona that had a role within an organization. And their query patterns were very predictable. And whether or not you ran a report or you looked at a dashboard, agents don't have personas. And so while you would try to create a dashboard, you don't have a dashboard. And so while you would traditionally use a specific application for observability or data warehousing or CRM, agents expect that they're going to traverse across all these applications. And they're not going to be constrained by access. They're not going to be constrained by latency. The experience is going to be defined by the slowest point in that chain. And so what's the number one requirement for agentic query patterns? Low latency. Because they're executing dozens of SQL queries simultaneously across all these different systems. And the most important requirement is the unpredictability of those query patterns, the responsiveness, and the fact that they're much more exploratory than a traditional human
Speaker 2report or query. Can I ask you, when you see the explosion of agent queries in this way, you'll also see the increasing awareness from agents to be more cost efficient. To what extent do you think you see a race to the bottom on pricing with the awareness from agents that they can't have an explosion of queries and cost being the same?
Speaker 1Well, I don't see agents necessarily being cost efficient. I don't see them thinking about consumption and budget like humans do. They and my mother have that in common. But the volume of queries is exploding at a rate that we've never seen. And so it's requiring these systems to completely rethink their pricing models, their consumption patterns, access patterns. And not only are agents hammering these services in an unprecedented way, but they're actually now selecting the underlying infrastructure. And so while you could go to or you could go to chat GPT and say, you know, what technology should I use for this specific use case? I'm thinking about a future where the agents actually select the infrastructure stack behind the application and positioning ClickHouse to be the default database for the next generation of applications that agents are building, not humans.
Speaker 2And just so I understand, when we fast forward to that three-year preference stack for agents, it's number one, latency. It's number two. Efficiency. Efficiency.
Speaker 1Yeah. I mean, Tesla, for example, is ingesting a billion events, per second into ClickHouse. That throughput is unprecedented. And so you need the ability to both ingest that efficiently, store it efficiently, and then be able to query that efficiently at a fraction of the cost of traditional database technologies. There just isn't another technology in the world other than ClickHouse that can satisfy those requirements.
Speaker 2When you think about that agent buying process, trust and security are so important. Everyone is saying that we're at this golden age in terms of cybersecurity, and we see more and more security hacks. How do you feel about the security vulnerabilities that come with the agentic future that you are planning for in three years out? More on the enterprise side. We obviously see it on the personal side, but more on the enterprise side.
Speaker 1Well, I think it's going to require multiple deployment models. So you need to be able to consume services via a cloud offering through any one of the three major hyperscalers. You're going to need the ability to manage that data on-prem behind your VPC in your firewall. So you're going to need to have the flexibility to deploy these applications as you best see fit, especially in the enterprise, where you've got highly, regulated industries, a lot of data privacy concerns, a lot of compliance requirements. And so as a supplier to these customers, we think about how do we support them dependent on their deployment preference? And that's a tricky roadmap to maintain because most companies pick one of those avenues. I mentioned Snowflake and Datadog. They're primarily cloud services. You look at more traditional technologies that run on-prem. And so if you force your customer into a specific lane, you're limiting the addressable market that you can go after.
Speaker 2You look at the agentic future of the three to five years that you're planning. What seems insane today that you think will be quite commonplace in three to five years?
Speaker 1We can talk about the fact that agents will need to have an identity that they don't have today. They'll need to have a budget. And how do you authorize an agent to consume services? Would you mean agents need to have an identity and a budget? If you ask Anthropic how they chose to use ClickHouse, they'll tell you they asked Claude, what technology should we use for this specific observability use case? And Claude suggested ClickHouse. I'm thinking about a future where they say, hey, we need to build an application, provision the underlying stack. So you've got a database, you've got networking, you've got compute, you've got storage, and the agent's actually making that selection process. But they need to have authorization. They need an identity. They need to have a budget to be able to consume those services. We're not there yet today. So if I were in your shoes, I'd be thinking about what companies are best positioned to give that agent everything they need to build a software application.
Speaker 2I'm sorry. Help me understand. Where should I be looking then? And why is that not included in the harness? Why is that not in the settings and preferences of the harness and the model provider?
Speaker 1Because most companies aren't just going to let their agents run wild and build whatever they want and consume as many resources as the agent deems fit. There's going to need to be some sort of governance and oversight with that consumption. And we're not there yet today. There's some human that is observing that consumption. They're monitoring the agentic spend. They're putting controls in place to make sure that things don't get out of hand, that they don't access enterprise data that they shouldn't. And they're not going to be able to do that. So I think it's going to be important that they don't spend a certain amount of money that they're not authorized to. If you look out three to five years, those agents are going to be fully autonomous.
Speaker 2When we think about one that I think is very clear is also like specialized models. We both know Linux Fireworks. I think every company will have their own model trained on their own data. They'll supplement their own data with additional data. But I very much see that being common. Do you see a world of millions of specialized models? Do you think you actually have your anthropics and your open AI's take the large majority of enterprise and only very specific cases have specialized models? How do you foresee that given the access point you have?
Speaker 1I think we're going to have both. I think you're going to have specialized models for specific use case like legal tech. If you look at Harvey, for example, I know they're, I think, leading the category in terms of specialization. But I think the large frontier labs are still going to be the
Speaker 2dominant providers in the space. Can you help me out here? I'm an investor in Legora. Why is that a better approach than Legoras, who obviously have not decided to dedicate their resources to building out specialized models? They consume less ClickHouse is the short
Speaker 1answer to me to the question. We're an infrastructure provider. So like we're picks and shovels, ClickHouse. So we're not like picking winners in these categories. Legora could be a bigger company than Harvey a year from now. I can't predict the outcome of these specialized providers. I don't know their revenue scale. What's the average customer spend on ClickHouse? It's a good question. So we define a customer once they hit a certain revenue scale. We've got a long tail of customers that consume some of our services, but once they actually are in production at scale, we count them as a production customer. There's a chart that you can see with our revenue growth and our customer growth. And you can see they're growing at a similar rate, but revenue is actually growing a little bit faster because our customers are growing faster than new customer acquisition, which is the most important function for a company of our size is how many new customers can we onboard in any certain period? Because we've seen the expansion characteristics of these services are unlike anything I've seen in my career. We had over 130% net dollar retention at previous companies. We're over 200%. Because these use cases expand, you could be using us for data warehousing. Then you use us for real-time analytics. Again, these historically were like siloed applications inside of an enterprise. People are now saying, we want to put all of this in one data repository. We want to build applications against it. We want to expose it to our customers. We want to expose it to our partners. And so we're just seeing this rapid growth. Average customer spend, I mean, we've got customers that spend tens of millions of dollars with us every year. We've got customers that spend thousands of dollars with us every month and everything in between. So averages can be a little bit misleading. If I were to look at the midpoint, probably around $100,000. When they are making that buying decision, which competitor do you fear the most? The one that isn't in the market yet. Like our competitors are right in front of me. I can see them. I know their strengths. I know their weaknesses. And what I worry about is the technology coming from the rear view mirror. I worry about the next click house. Like people really didn't see this technology coming. It was open source 10 years ago. That's when I first discovered it. It burst on the scene. Thousands of companies adopted it. But there was no company behind it. And so people dismissed it as just another popular open source database. There's been a lot before it. There will be a lot more after it. So I worry about what's the company that's going to disrupt us in the same way that we're disrupting the competitors
Speaker 2in front of us. You mentioned obviously click house being an open project and the amazing early traction that you had. When we look at the percent of tokens that are now going through open models, it is increasing exponentially almost it seems. And it is removing from frontier models. What percent of tokens will go? Through open in three years versus frontier?
Speaker 1Well, the easy answer is 50/50. In the same way that what percentage of enterprise software today is open source versus proprietary? I think it's a pretty even distribution. That would be a controversial prediction, though. I don't know. Look at the big two data warehousing providers, Snowflake and Databricks, right? Snowflake is primarily a closed ecosystem. Databricks is built around open source. Would you argue which one's going to be bigger? Databricks. Perhaps, right? But then you add Datadog. Datadog's primarily proprietary. Other open source observability tools are open. Which one's going to be bigger? Databricks. In observability, I would argue Datadog over Databricks. I just think Alibaba. Well, you never know. Three to five years is a long time. It's a very long time. I don't want to underestimate Databricks. It's a great company. Do you know what's shocking when you say that? It's like five years ago, ChatGPT wasn't out. That's the stark wow. I mean, are they going to get into infrastructure? Will they be offering databases as a service? I don't know. I wouldn't dismiss Anthropic and OpenAI as core infrastructure providers. Right. Really? Yeah, not at all. I don't see them as competition today, but you see how they're entering new categories so quickly. Just imagine the surface area they're going to cover in three years.
Speaker 2Building their own chips. This would not be extraneous. Yeah. Totally get it. But the conventional wisdom would be that you see 90% through open, 10% through frontier. In the conversations that I have today, everyone basically says frontier models will be used for cancer, climate change, extremely valuable, but very few tasks. And then, the rest of everything will go through open. You don't agree with that?
Speaker 1I don't, especially in the enterprise. They want provisions and protections that potentially open weight models, especially those that come out of China, cannot provide around indemnification, for example, and output inference. And it's going to limit the use cases that those open weight models are adopted for. Now, again, it's very important that we distinguish between open weight models and open source software. Okay? We're in the latter category. My predictions on enterprise adoption around open weights models is very different.
Speaker 2For those that do not know, and I like to be not just for Silicon Valley inner engineers, open weight versus open source in a minute.
Speaker 1Let's focus on open source. So open source is essentially where anybody can inspect the source code. Anybody can modify it depending on the license that it's governed by. You can deploy it with no attribution to the authors of the software. You can modify it. You can monetize it without any relationship of the people that are actually developing it. You can contribute to it. You can fork it. Now, open source licensing has evolved significantly over the last five years. That affects some of those implementations.
Speaker 2Okay. I'm pleased that you said that you don't agree with that. And actually, there will be more concern around using open weight models and potentially Chinese models. When I speak to people on the show, they actually say, that the biggest enterprises say I'm more scared to work with frontier providers than they are open source Chinese models.
Speaker 1Because people don't trust the statement zero data retention. It's basically you saying, just trust me. I got you. You know, some people will take you at your word. Many will not. And so I think a lot of companies worry about sending their source code, for example, to a frontier lab. Do you see that? I do. I see it every day. I mean, we have their own concern internally because you worry about the output from that code generation. You worry about, you know, third-party indemnification, if you were to consume code that's being derived from another repository. So what do you do in that case? You then go to an open model? You limit the use cases. You know, you can use it for code review, for example, but maybe not to push production code into an environment that your customers are using.
Speaker 2But then what do you trust? You trust an open Chinese model with the more sensitive data? Because again, this is what someone said it on the show that I was like, now you must have got that confused because they said for all like less sensitive things we use, you know, anthropic. And then for everything more sensitive, we use an open source Chinese model. And I was like, you mean the other way around? And they were like, no, no, no, that's the right way around.
Speaker 1I think when you need the legal protection that most enterprises do, you're going to want to work with one of the frontier lab providers. I think there's too much security concern around some of these open weight models. Is it justified? Today, I think it is. If I look out a year or two from now, I think a lot of these concerns will be addressed. You don't buy the back door to the CCP? I personally don't like to speculate that, you know, by using some of the software, you're somehow going to be engaging in some nefarious... Chinese espionage.
Speaker 2Exactly. I mean, it's quite fantastic to go there. Listen, you're CEO of one of the kind of most prominent open companies in the world in terms of ClickHouse. When we look at the American open models, we significantly lag behind. If I were to say, Aaron, I want you to spearhead open American models, what would you do to encourage, incentivize us to dramatically leapfrog China now in our open ecosystem?
Speaker 1Well, obviously, I'm a huge fan of open source and open weights models. So I don't think that any sort of government intervention is wise in terms of limiting the adoption of these technologies, the distribution of these technologies, because I do think, you know, open source and open weights models are the future. And the future is defined, I don't know, three to five years. It's really hard to look out further than that. I personally wouldn't take your capital and say, hey, I'm going to deploy it to develop an open weight model. Do you see more and more enterprises want to go back on-prem in this day and age? We do. Yeah. And even companies that I thought would never be going back on-prem are talking about going back on-prem. Like some of the most innovative digital native companies in Silicon Valley are now thinking about moving their stack from, you know, one of the hyperscalers to an on-prem environment.
Speaker 2When we think about agentic workflows, a lot of what we've said, kind of agent identity, how sophisticated are traditional enterprises when you speak to the CEOs, when you sell to them, what you see and what's the chasm between what you see and what they know?
Speaker 1Narrow. It is. Yeah. I mean, I was at Canary Wharf yesterday, meeting with some of the largest financial services companies in the world. They are leading the way in terms of their adopting new technologies in a way that I've never seen in the past. A lot of the times, historically, the sales cycles into these big firms would be measured in years, not quarters. They're now adopting technologies much faster than they ever have before. So you're seeing sales cycle compression in this day? Yeah. I mean, open source aids in that, because you can get started without any sort of vendor relationship. PLG products like Datadog and ClickHouse aid in the fact that you can just spin up an environment without ever talking to anybody in the sales organization. You can have this frictionless experience to where you can evaluate, deploy, scale the product without a traditional enterprise sales process.
Speaker 2I think people just fundamentally misunderstand the GTM and the business behind it. What do investors get most wrong when analyzing your business?
Speaker 1Investors often say, where's the moat? How difficult would it be for me to simply redistribute ClickHouse? What's the risk about one of the hyperscalers offering ClickHouse as a managed service? It's been done before where AWS or Google or Microsoft takes your open source and they redistribute it as a managed service. So now you're almost competing against your core database. That has been an issue in the past. I think if you can maintain a competitive advantage with your cloud offering or your proprietary features that are very, very difficult to replicate, then you can maintain that moat. And I think very few open source companies get that right.
Speaker 2I do want to weigh in. transition back but when we said about kind of agent preferences and agent you know anthropic using anthropic to choose click house does that mean like developer relations developer community becomes less important and how does the future of brand change when agents become decision makers
Speaker 1so i talked about you're building an application like let's you're building a dating app right so you can build it over the weekend you can vibe code it right and in theory that agent can select the stack right it can select a managed postgres service because you want to support transactions it can a managed click house service because you've got analytics and everything in between you still have an enterprise buyer you still have a huge data warehousing project at a top bank or a telco that's going to be driven by an engineer or a developer and there's still going to be a human that's making that architectural decision on are they going to use click house are they going to use snowflake are they going to use data bricks you've got an observability workload are they going to use something off the shelf like splunk or datadog or are they going to embrace open source and use something like click house for the next decade there will still be a human involved in that decision loop so it doesn't change the investment and commitment that you have towards brand not at all because budgets are still controlled by people right and budgets correlate to technology decisions and so a few years ago i started doing things around awareness like for example for aws reinvent amazon's big cloud conference in las vegas or google next i partnered with the chain smokers and i had them perform because i said there's not one party that everybody at reinvent wants to go to it's a bunch of like shitty restaurant buyouts and happy hours i want one party that 60 000 software engineers are jumping over themselves to get access to so i partnered with alex and drew and we started performing these concerts and they started performing these concerts in support of click house so then i thought about how can we even drive broader awareness and so a sports sponsorship came to light i'm not the first person to do this as you know you know a lot of other companies are doing this and i'm not the first person to do this as you know you know a lot of companies that are sponsoring premier league teams sure we did a financing earlier this year and then we extended it and brought in some strategic investors like yourself and david sacks and michael dell and jp morgan we didn't need the capital we had a billion dollars on a balance
Speaker 2sheet i quite like the affiliation to those names so thank you very much for including me david sacks
Speaker 1and jp morgan and very helpful happy to so i thought what better way to spend this new investor money than to sponsor an english premier football club in london why football why english premier league you're not going to be able to do that you're not going to be able to do that you're not you can sponsor f1 you can sponsor your laguardia golf as well why football i love the sport but let's put that to the side for a minute i think the value of these sponsorships obviously come in two forms the first is awareness and as we saw last night against chelsea this is a game that's being televised globally so you've got millions of viewers that are looking at your brand you're getting impressions obviously the second which is obviously easier to quantify is hospitality and we're sitting here at craven cottage along the thames i think this is arguably the best sports experience in the world and i've been to many we had 20 executives last night attend an intimate michelin grade dinner you know the c-level executive come from paris one of the largest banks in europe just to experience that those types of relationships are extremely
Speaker 2important especially as we move up market do you think we will see the price of sports assets dramatically increase even further still we had obviously the not coastler buy i always get it wrong but i'm a brit so forgive me it's not the seagulls it's the seahawks yeah seahawks
Speaker 1yeah which obviously i didn't love to see considering both coastal as an investor in click house but he was a minority owner in the 49ers why is that bad why didn't you want to see it because i'm a san francisco 49ers lifetime faithful i'm from fulham i don't have a clue i thought it was the seagulls well it'd be like well you know you turning around and investing in chelsea for example you wouldn't do that obviously as a fulham supporter i obviously
Speaker 2would not do that right no unless there was significant monetary gain in which case i'll do it in a second well but those are very savvy businessmen so i'm sure it's going to be a good investment for him josh buys the lakers for 12 and a half and i'm like to the point of like underestimating where value accrues jim will see 20 billion dollar sports teams i do i mean we just
Speaker 1saw that with the lakers i think it was the most expensive sports transaction in history 12 and a half it was reported that the seahawks sold for 9.6 billion it's all obviously it's well reported what the english premier clubs trade for i do think that i mean it's a experience you simply can't replicate through technology or anything else there's something very visceral about it we felt it last night to be there at the pitch 28 000 rabid fans on their feet to launch the premier season southwest london derby chelsea versus fulham three to two five goals like what more could you
Speaker 2ask for i totally agree and i think also in the world of ai you actually crave those experiences more that and music in particular i think will be two of the most kind of blossoming totally get you there how do you think about like spend for it i'm not asking you how much you paid for it but like how do you think about roi effectiveness on we're going to commit
Speaker 1a lot of budget to being in front of shirt well you know we had 20 guests last night budget owners from some of the largest companies in the world half of those are customers half of those are prospective customers so i can very easily measure the spend that i can gather from that basket of accounts over the next 12 months how much of that do you solely attribute to a sports sponsorship that's very difficult to assess we could see top of the funnel metrics improve in terms of website visits new trials that could be a derivative of the awareness that we're driving through the sponsorship kind of one of those two ways if not both dude i was talking to your investors and
Speaker 2many of them said every round i've wanted to invest more in in aaron and click house and he always cuts me back what do you know now about fundraising that you wish you'd known when you
Speaker 1started the credit really goes to yuri and alexei then my two co-founders are spectacular the best engineers i've worked with in my career are the best engineers i've worked with in my career are the best engineers i've worked with in my career by a very wide margin and so i'm happy to be the interface to the investor community and maintain these vc relationships but really it comes down to how differentiated our engineering culture is in terms of cutting back investors i mean as you know when i evaluate an investor relationship it really boils down to the value that they're going to bring the customer introductions that they're going to make the advocacy that they're going to help with how do you determine that everyone sells a good game vcs we sell cash we get good at selling i reference them like you would if you were a real investor if you were a real investor you would in any other relationship so i talked to the companies that they've invested in in the past i say what's it like to work with harry what customer relationships has he made that have been valuable has he helped with awareness from his social presence has he helped with recruiting how does he work with other investors do people perceive it as a positive to have men on the cap table and those all need to be a unanimous yes before we start working together do you think he
Speaker 2raised aggressively enough we're seeing a new world by capital it's more and more remote in a
Speaker 1lot of cases you know i'm trying to build a generation of investors who are willing to work with me and i'm trying to build a generation of investors who are willing to work with me right now a lot of people look at fundraising as a very short-term exercise and they want to have this consistent and steady step up in valuation it's good for your employees you give them liquidity through tender offers it's good for recruiting it minimizes dilution it bolsters your balance sheet it lets you forward invest all of those things are true but i'm thinking about a company 20 years from now not two years from now so whether or not we raise that 15 billion or 25 billion in 10 years is irrelevant right we need to have the right investors involved we need to have the right investors involved we need to have the right investors involved we need to build a very durable long-lasting sustainable company we need to get to a billion dollars of arr as quickly as possible the most important metric for the company is new customer acquisition we had hundreds every month our gross retention is north of 99 percent our net dollar retention is north of 200 percent the addressable market we're going after is absolutely enormous so i think less about valuations perhaps than i should when will we hit a billion an hour within the next two years if not sooner give me a date we can do it back we can both do a bet i'd put the over under at december 2027 and i would take the under you think you'll get
Speaker 2that before i do i'm gonna go for feb 28. i think now it's like 18 months that's more than 18 months
Speaker 1yeah it's 18 months i would definitely take the under on that time frame what do you mean oh yeah
Speaker 2250 now we're well north of that oh well that's unfair you said they're about tenders we see them more and more for employees and i think talent acquisition is one of the hardest things today i actually got in a lot of trouble the other day for this i said if you are trying to hire a star talent today you can't open ai and anthropic simply pay and they go to the front-end model providers is that true or was i being glib i think it's true depending on the category that you're in
Speaker 1i think if you're a digital native ai startup in san francisco it's a very difficult employment environment because you're competing against open eye and anthropic and others that are extremely well capitalized and are putting offers that are extraordinarily aggressive into the market that's why i think it's really important that you're doing that you're doing that you're i think if you're a infrastructure provider like click house we look for a slightly different profile you know we're looking for database engineers people that have experience with distributed systems slightly different than what the frontier labs are hiring for we employ people in 27 different countries which gives us a competitive advantage so i can hire engineers in portugal and germany and singapore you know we've got single digit attrition so we've got extraordinarily high retention we have done some structured secondaries and we'll continue to do so over time but not with the frequency that i think's going to be the most important thing
Speaker 2some of the younger companies are doing so i'm you know controversial in many ways one of them is because of my vocal expressions about remote work why am i wrong i don't think you're missing
Speaker 1anything i'm of two minds and i contradict myself constantly about this topic because i spent 12 years at salesforce i was in the office every single day five six days a week 10 12 hours a day and it was during this extremely formidable time in my career i learned so much from those experiences being in the office amongst my colleagues and peers and i've been able to learn so much over the years learning from people with more experience than i had at the time when i started this company was during covid and so we kind of had to be distributed by design and i started it with some europeans and so people were in europe i was in the bay area my co-founder was in Utah. We started the company. We grew very quickly, found engineers that had a very unique skillset, and they weren't all in the Bay Area. They weren't all in London. They weren't all in New York. And so we built a distributed company. Fast forward to where we are today. We're almost 800 employees. We'll be 1,000 by the end of the year. We are introducing in-person options for our employees. We don't have this draconian return to work mandate or return to the office mandate, but we do have offices, and we have a huge office in Amsterdam. We have an office here in London, New York, the Bay Area. Is that specialized around different functions? Not at all. Really? Yeah, both engineering and go-to-market. And we're seeing increased participation across the employee base and increased demand for office space. And if I look at a year from now, we're not going to have six or seven hubs. We have an office in Singapore. We have an office in Sydney, Australia. We have an office in Tokyo. We're not going to have six or seven. We're going to have 16 to 20 offices around the world within 12 to 18 months. If you could have your way, would you not have everyone be in office in some way? I wouldn't, and I'll explain why. We're a very international company by almost every measure. Over half of our revenue comes from outside of the US. 40% here in EMEA, 10% in Asia. Over half of our customers are outside of North America. And so we need to support our customers in a variety of different languages, in a variety of different time zones. I mentioned we're live in 36 different regions around the world across all three hyperscalers. There's no way that you can centrally manage that from one location. You need to have people in every single time zone. You need to have relationships with the hyperscalers in region. We go to market with AWS. We go to market with Google Cloud. We go to market with Azure. I flew to China to launch a partnership with Alibaba. You're going to need local language speakers to maintain those partnerships. And you can't do it from one or two or three centralized hubs. What phase of company growth was most uncomfortable? When were you the teenager at the wedding? The most uncomfortable phase was immediately following our product launch. It was at the exact same time ChatGPT launched. And these database services are different than consumer services. They take time for companies to evaluate and adopt. It's not like you're just going to use ChatGPT overnight. You're going to get to 100 million users in two months. So there is this six-month period, and it shows up on that bar chart of revenue growth, where revenue was slow out of the gate. Now we've hit this inflection point and revenue is surging now that we have over 4,000 customers. But those first six months, you know, I raised $300 million at evaluation. That was hard to justify because we had no
Speaker 2revenue. We had no product. Your prices were quite chunky. I mean, at like $50 million in revenue, you were priced like $6 billion. Again, just a point in time. Like, you don't get credit for where you are. When my LPs are like, dude, but your DPI is not what, you know, Gilly Renanzas. I mean,
Speaker 1it's a point in time. Right? Yeah. But you're giving credit for the next year, right? And that's how venture investing works, in my experience, on the other side of the table, which is you're not getting priced for where you are at that point in time. Right. You're getting priced for where you're going to be in 12 to 18 months. And if you have a track record of execution and you have a track record of overachieving against your targets, then you can garner a multiple that is disconnected from the public markets. Which round felt most expensive and which round felt most cheap? The Series B that KOTU and Altimeter jointly led at $2 billion felt expensive. We had no revenue. We had no product. We had control of an open source database. We had no customers. We had 15 employees. So that one, I felt like put a pretty big target on our back. And that's when the pressure really started to mount on building this differentiated product. And it took us a year. Those were some long days, you know, thinking about when are we going to get this product into the market? What's the customer reception going to be? We knew there was some latent demand. I didn't anticipate there was going to be this much sustainable demand three and a half years later.
Speaker 2Also, you didn't know that the AI wave was coming in the way and speed that it has done, which has been the propulsion of all generation.
Speaker 1This was five years ago. I had no idea. I knew that ClickHouse was the most resource efficient and performant database in the world. And so I knew that it would satisfy whatever trend was going to come. Because in the database world, it comes down to price and performance, a lot of other attributes in terms of feature completeness, et cetera. But that's really what it boils down to. And I knew that ClickHouse had an advantage on both.
Speaker 2Which one was the most cheap round? Probably the current one. Yeah, I felt this too. And I know it's obviously, it's a lot of money in terms of $15 billion. But when you look at what you have, the customers, the revenue, the slope, I'd much rather pay more for more than less for less. Does that make sense? It does. I totally get that. Can I ask you something I struggle on? Another thing that I get chastised for is you said about the infrastructure slope on revenue, or the slope on revenue being slightly slower because it's an infrastructure play. I often say that triple, triple, double, double's dead. You know, the one to three to nine to, it continues, is dead. And we need to be zero to a hundred million in a year. Now, am I glib and wrong, and that won't take into account infrastructure plays, or is that actually just the new world that we're in?
Speaker 1Well, as I mentioned previously, I think the durability of revenue is the most underestimated attribute of these companies, meaning how high are the switching costs when somebody's using your product? And for any category that goes from zero to a hundred million in a year, I worry, what's the competitive moat that they have to preserve that hundred million from that customer going to something else? Yeah. Yeah. Yeah. Yeah. Yeah. And ours was a bit more gradual. We went zero, 12, 50, 200, and we'll finish this year north of 500, which in the database world is faster growth than we've ever seen, including all of the competitive companies that I mentioned earlier today, in terms of the first three years of revenue growth. And it's over a very broad customer base. So we've got very little concentration risk. The basket of AI companies that's using us, and nearly every AI company is built on ClickHouse, from Harvey, Sierra, Decagon, Anthropic, OpenAI, et cetera, represents less than 12% of revenue. And so even if half of that goes away, the winners are going to offset the loss from the losers.
Speaker 2Is concentration risk a valid investor concern? You see a lot of people say like, oh yeah, I'm an investor in McCore. Oh, McCore's 90% of their revenue comes from frontier model providers. And like, so does NVIDIA's. Seems to be working for Jensen. Is concentration in terms of revenue a valid investor concern anymore?
Speaker 1I think about it as an operator, as a very valid concern. If I've got one customer that, or one category, or one industry that accounts for more than 10% of revenue, I spend a lot of time thinking about it. And that seems to be kind of the industry standard, that threshold, that if some dimension of your revenue base accounts for more than 10% of your revenue, you've got exposure. And I want to limit exposure, right? The goal is predictability, sustainability, durable growth. And if I've got one category or sector or customer that can have such a negative effect, if they were to leave the platform, that's a concern for me.
Speaker 2We said about switching costs there. And I think one big mistake often investors think is, ah, you know, once I get to a certain scale, I'm going to move off Elastic and build my own. Once I get to a certain scale, I'm going to build my own payments processor. Shopify still use Stripe at the scale that Shopify is at. And actually, most often, you just don't because it's not your core business. I'm intrigued how you think about that, especially given your time with Elastic and whether we do overestimate the,
Speaker 1I'll just move at scale. It comes down to customer value, right? You need your customers to continually see value from your service, which means you always need to be ahead of your competition in terms of the ROI and the TCO calculation that your customer is going to think about. Total cost of ownership. So if you think about how much does it cost to run ClickHouse, how much does it cost to run a comparable service, and you want to have that advantage. Those are the two primary attributes that you're going to think about in terms of value creation for your customers. Do you think it's important to have an internal enemy? I don't. I worry about creating adversity inside of a company. Well, you have so much adversity outside of your company, right? You've got to deal with competitors, disparaging yourself and the company. You've got to think about how you stay ahead of the competitive landscape. You've got to think about geopolitical concerns. And that's before you have any sort of personal strife in your life. That's just work. So why would you want to introduce that into your company? To create fire in them that they want to beat someone. Oh, that just comes down to hiring the right people. Like we only hire people that are insanely competitive. Has your hiring changed in an AI world? How you determine talent? How you discover it? You know, I think we're a little bit unique. The average age of our engineering organization is in the mid to late 30s, which is a little bit different, I would imagine, than a typical venture-backed company that's only had a product for three years. So we typically look for people that have a bit more experience. It's not to say we don't bring people into the company straight out of college, but we want to make sure that they're paired up with somebody that's been building distributed systems for a period of time. A lot of people question the value of college today, do you think that's justified? It's something I think a lot about. We've got two teenage daughters. And so, as they think about college- Would you tell them to go? I would, but I think it's simply around their life experience. You know, the, and again, I don't want to take anything away from like the academic output of a four-year degree.
Speaker 2But with the greatest of respect, you should. And I mean that, again, this is why you're popular and I'm probably controversial. Like you should, the curriculum process to update them is so long that by the time it's been updated, it's already out of date. I think it depends on what you want to study.
Speaker 1Well, if you're studying obviously neuroscience, then it's relatively important. Yeah. If you want to go into medicine, I think that we're going to need doctors. You want that human interaction, right? If you're studying software engineering, I think you're going to be entering a market that's very uncertain in four years' time.
Speaker 2Do you think this could all get a bit creepy? You said that we're still going to need doctors. Well, I'm not really so sure if I'm totally honest. I use ChatGPT for most of my medical queries now, and it prevents me from seeing a lot of doctors. Doctors are pretty unaffordable to most people. Wait times in the UK for a GP are months. Yep. I don't know. no, dude. And Dario wants to cure cancer. So I think he'll fix GP appointments, won't he?
Speaker 1If I've got a serious medical concern, or I need some very important legal advice, I want to talk to the best lawyer in the world. I want to talk to the best doctor in the world. And that's not going to change for me personally. Now I represent a slightly different generation than you do. So that may be different for people behind me in life. But I do think those domains are quite durable. Do you think it could get creepy though, with the AGI realization coming true? I don't. I think robotics would be probably more disruptive, frankly, to the medical industry. We had a family member have a procedure that was done entirely autonomously with just a doctor overseeing it, but didn't actually touch an instrument. And I think that will be the future.
Speaker 2So listen, we're going to do a quick fire round. So I say a short statement, you give me your immediate thoughts. Does that sound okay? No, why not? What job does not exist today that you think will be extremely effective in the future? What job is extremely common in five years?
Speaker 1An AI finance function, solely dedicated on AI consumption inside of an organization. That's all they wake up thinking about. In terms of token resource management? Correct. And then that job will be made irrelevant five years from then, because AI agents will govern themselves. Which job will never be made irrelevant? VCs like to think it's ours. Professional football players.
Speaker 2Dude, I'm 30. It's too late for me now. Professional athletes. I'm going anywhere anytime soon. In the UK, we have a game. It's called, forgive the crassness, Shag, Marry, Kill. Shag is short-term buy. Marry is long-term buy. And Kill is a la poubelle. No, not for me. You have Meta, you have Microsoft, and you have NVIDIA. What is your Shag, Marry, Kill on them?
Speaker 1Which one would I shag? Which one would I marry? And which one would I kill? Well, Meta's a customer, so I don't want to put them in the latter category. Microsoft's one of our power users. We power the largest analytical workloads at Microsoft. So I'll probably marry Microsoft. I had the opportunity to meet Satya a couple of months ago. It was quite impressive. We do business with both NVIDIA and Cerebrus and a lot of the chip manufacturers. I mean, I'd like to shag all three of them, but unfortunately, I don't think that's possible.
Speaker 2Do you think we'll see a much more distributed chip ecosystem in the next few years? You see Etched and you see a lot of other providers, Cerebrus being one of them.
Speaker 1Yeah, absolutely. Yeah, I think a lot of the hyperscalers and frontier labs are going to be very relevant providers in the chip ecosystem.
Speaker 2What's one widely held belief about AI that's pretty agreed upon that you think is actually pretty wrong?
Speaker 1A widely held belief around AI that's generally agreed upon but is wrong is that it's overblown and that we're in a hype cycle, that we're in a bubble. And I'll kind of finish it with where I started. We're just getting started. You know, I can't pick the winners and losers, but I think the winners are going to far offset the losers.
Speaker 2Do you worry about the levels of debt being taken out exceeding any historical norms?
Speaker 1I worry about the public exposure to these companies when they're publicly accessible. Right now, it's private capital. And so, you know, a lot of investors stand to lose money. A lot of investors stand to make a lot of money. Totally. But NVIDIA represents a huge amount of 4098s for a lot of Americans, right? Yeah. But NVIDIA is a public company, so they've got public disclosures, and that's different than the private markets.
Speaker 2Sure. But if it were to take a hit, you would see mass wealth or kind of monetary impact.
Speaker 1Well, that's the case with any sort of inflated asset. I'm not suggesting NVIDIA's inflated.
Speaker 2No, but if you see the concentration of value into a few names in this way, like we've never had 85% of the stock market's value predicated in six companies.
Speaker 1Yeah. But look at the value creation that's occurred over the last 10 years. Is there going to be some sort of compression? Possibly. You know, are you going to get back to the levels we were at 10 years ago? Highly unlikely. What's the biggest lesson from Peter Fanton? Peter's great. He's on my board. This is the second company I've worked with. Yeah. This is the second company I've worked with him at. You know, Peter's very philosophical. I compare and contrast him to Mike Volpe, who's also on my board. And Mike was an operator, worked at Cisco for a long time, ran Corp Dev. I think he did over 100 acquisitions. Yeah. Peter is a career venture capitalist, and he's helped shape and form some of the most influential and impactful companies in technology. And so he has this amazing pattern recognition to where he can, A, he's an incredible talent magnet. He's been great for recruiting. When you get him on a call, when you get him on a call with someone, what are you asking him to do? Determine if they're good or win them over? Well, I typically tell him whether or not he's buying or selling, whether or not he's trying to convince this person to join the company or really evaluating this person critically. And that's going to influence, I think, how he approaches that conversation.
Speaker 2Who do you not have on your board that you would most like to have on your board?
Speaker 1There really isn't anybody that I would put on that list right now. I'm adding somebody to the board shortly that we're going to announce I'm really excited about. When I was starting the company, I met with a variety of different investors. Mike and Peter were the first two that I called. I met with Martin Casado in Andreessen, who's a friend of mine. And I would have loved to have him involved because I think he understands what we do in a very unique way, technically. Why is he not involved? He was conflicted at the time. Ah, bugger. I know. It worked out fine. What concerns you today, Aaron? You know, what I mentioned earlier today, like the competitive landscape, I can see it's clear as day. It's right in front of us. I know how we're going to execute against them. I worry about the technology that isn't yet in the market and that's going to emerge. And how defensible our position is against that, because that's what we did. We burst onto the scene. Nobody anticipated this was going to be a company that's experienced such success and delivered such customer value. I worry about what that company is going to do that's undefined. And so I go to the company and say, we need to constantly think about reinventing ourselves to be that disruptor so that we can basically disrupt ourselves. If I could erase one name, Snowflake or Databricks, which one would you rather I removed? Removed from the market? Well, I think. It's well documented that Databricks is executing extraordinarily well in the market. I've got a ton of respect for Ali and the company. We're going after adjacent markets. These are database technologies, so you squint hard enough, there's going to be competitive overlap with all of them. There's plenty of white space on either side of the Venn diagram with us and Databricks.
Speaker 2Dude, you're CEO of a $15 billion company, one of the fastest growing technology and an incredible business. You also have two incredible children. What's the biggest advice on how to be a great CEO? What's the biggest thing you can do to be a great CEO?
Speaker 1Well, I think the attributes are very similar. You know, you take your job seriously and you commit to it and you think about how you can improve and you ask for advice and you surround yourself with people that have experience doing whether it's parenting or running a company and you replicate the best attributes of those people and you leave the other ones behind.
Speaker 2What do you know about marriage now that you wish you'd known when you got married about what it takes to be successful?
Speaker 1We've been together for 24 years. The acceptance that it's not a straight line. The willingness to come together with that understanding and embrace one another's differences, celebrate the achievements of the individuals and the relationship and realize that you have a shared purpose, especially when you have kids. It's a very powerful shared purpose. And that's very similar to running a company. You know, you want all of your employees to be aligned with the objective. And what is the purpose? What's the vision? How are we going to get there? How are we going to execute? Final one for you.
Speaker 2What are you most excited for when you look forward the next three to five years? You just met my mother, which is awesome. She has MS. I'm excited for potential breakthroughs in chronic conditions, which have traditionally just always been incurable. What are you most excited for?
Speaker 1Well, if you'd asked me that question five years ago, I don't think anybody would have predicted where we are today, right? I mean, ChatGPT launched in November of 2022. That's less than four years ago. So looking out five years from now is nearly impossible. Obviously, the same medical advancements is important. I'm looking forward to a Fulham Premiership Championship, looking for qualification to Champions League, winning the FA Cup. I'm looking for the US to advance further in the World Cup in four years when it's in Spain and Portugal and Morocco. Where will ClickHouse be in five years' time? I think, you know, I'd take the under on being a public company. We could take the company public next year if we wanted to. There's no rush. Why would you not? I think if you're looking at the world in, you know, three to five year time horizon, that applies. Again, like I'm hoping this company outlives me, in which case whether or not we go public next year in five years is pretty irrelevant. I mean, when Salesforce went public in 2018. In 2004, it had a billion dollar market cap. What do you think you get by being private? If you're ready to go public next year, I completely agree with you. Well, the markets are more irrational now, I think, than they've been in a long time. And so it's pretty rough being a public company. Like your stock can trade down 40, 50% on a slight miss in a quarter. And we know that impact on employee morale. And you don't have that in the private markets. It is brutal. Every CEO is like, oh, no, they're heads down. It doesn't matter. It matters. I've come full circle on this. Like I remember having dinner. With all the a few years ago, and I asked him this question. I'm like, I feels like you guys are ready to go public. And he said, I kind of basically run a public company and he walked me through that. And I said, well, there's really two dimensions that don't apply. You know, you don't have your employees looking at your stock price every day and you don't have anybody shorting your company. Those are two material impacts of being a public company versus being a private company. Now, the employee liquidity is more or less gone away because you can do structured tenders and you can give your employees liquidity over time. The bear thesis hasn't gone away. Like you don't have people. You're shorting your company when you're a private company. So you don't have to deal with that in your day-to-day course of work.
Speaker 2And then on top of that, a lot of people have traditionally said, well, the joys of being a public company is you have this kind of tradable currency that you can buy companies with, which is helpful for acquisitions. Yeah, well, Stripe is buying PayPal for $50 to $60 billion as a private company. Bit of an outlier, but I get what you're saying. And OpenRooter as well at $8 billion. Yeah. God, these are two pretty sizable acquisitions that traditionally would be unthinkable for a private company.
Speaker 1Now, my question would be, why would anyone go public? I mean, it's a valid question. I think, A, it increases awareness. It's a financing event. You diversify. your investor base it's very good for employee morale i've been through two ipos is it it's it's wonderful your community celebrates it your family celebrates it your friends your colleagues
Speaker 2from university like it is not a short-term thing though again to the point of the the tumultuous journey that comes post you're like great for a week and then at the whims of a volatile stock
Speaker 1market yeah but again i believe in the public markets i believe in the capital markets i believe that you know in terms of price discovery public markets are generally better than private markets in the long term they behave more rationally than private investors who are willing to pay a premium to get into a company betting on the come whereas in the public markets you're really getting credit for where you are at that point time maybe there's some speculation built into your stock price but it's more grounded in the execution and the results that you're delivering
Speaker 2totally get that listen you've delivered incredible results i have no doubt that you will win the bet that we have in terms of reaching the billion in air i look forward to wiring you a thousand pounds when you do but thank you so much for hosting us at fulham this is incredible it's a beautiful setting thanks so much for having me but before we leave you today founders face a different set of challenges at every stage of growth for sid shate co-founder and ceo of d matrix jp morgan delivered the guidance and expertise to help navigate what came next he credits jp morgan's high touch approach with supporting d matrix as it grew and expanded internationally whether you're in the early days or expanding into new markets jp morgan helps startups navigate complexity with real confidence offering personalized guidance and deep sector expertise find out how jp morgan helps founders at jpmorgan.com forward slash grow without limits jp morgan is the bank of the innovation economy while jp morgan powers your finances asana keeps the world going and he's been a big part of the work moving most companies have tried ai most aren't seeing results not because ai doesn't work it's because ai hasn't reached the workflows yet that's the gap asana is built to close asana is the operating system for human agent teams your easy button for ai productivity across every team ready to go ai teammates pre-built for marketing ops and it no prompt engineering no setup they show up where the work is happening already onboarded in your workflows ready to deliver it with asana your whole company can work on the same plan towards the same goal whether you're a team of 10 or a team of 10 000 asana where humans and agents work flow together try it at asana.com that's a s a n a dot com while asana aligns the roadmap base 44 helps you build faster you have the idea but with most ai tools you hit a wall the setup the config the gap between what you pictured and what you actually ship well base 44 is where that wall disappears you describe it yeah base 44 builds it apps websites ai agents real working products built in minutes using nothing but plain language and it's all batteries included the back end the database the authentication the hosting the heavy lifting is handled so you just really stay in the flow this doesn't just take the busy work off your plate but it gives you an advantage and pushes you past what you thought you could build alone so in this market fast is the baseline to win you just have to be first base 44 is that edge the move that skips the troubleshooting and gets you straight to the breakthrough build your next
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